Corporations and other types of organizations collect and store large amounts of data in order to manage processes and to monitor efficiency, productivity, and accuracy. The data tends to be managed by subgroups within the organization, often leading to non-warehoused data stored in disparate systems. Further, even in organizations wherein there is an effort to integrate data across subgroups, the benefits do not necessarily outweigh the costs. The collection and storage of data is an ongoing dynamic process, and sometimes an organization's data stores receive an influx of data from another source, such as when there is a merger with or acquisition of another organization. There are situations in which it is never cost-effective or realistic in terms of timeliness to fully integrate an organization's data systems.
Data that is useful to one subgroup is almost always of interest to at least one other group within the organization. However, it can be challenging to locate and retrieve non-warehoused data that is stored in disparate systems. Subgroups may therefore collect and store the same data redundantly, and may also expend resources crafting ways to search for and retrieve data that has already been retrieved by another subgroup. Thus, there is duplicative effort in collecting and storing commonly used data, and further duplicative effort in searching for data stored in disparate systems.